EEG signatures of arm isometric exertions in preparation, planning and execution

The electroencephalographic (EEG) activity patterns in humans during motor behaviour provide insight into normal motor control processes and for diagnostic and rehabilitation applications. While the patterns preceding brisk voluntary movements, and especially movement execution, are well described, there are few EEG studies that address the cortical activation patterns seen in isometric exertions and their planning. In this paper, we report on time and time-frequency EEG signatures in experiments in normal subjects (n=8), using multichannel EEG during motor preparation, planning and execution of directional centre-out arm isometric exertions performed at the wrist in the horizontal plane, in response to instruction-delay visual cues. Our observations suggest that isometric force exertions are accompanied by transient and sustained event-related potentials (ERP) and event-related (de-)synchronisations (ERD/ERS), comparable to those of a movement task. Furthermore, the ERPs and ERD/ERS are also observed during preparation and planning of the isometric task. Comparison of ear-lobe-referenced and surface Laplacian ERPs indicates the contribution of superficial sources in supplementary and pre-motor (FCz), parietal (CPz) and primary motor cortical areas (C1 and FC1) to ERPs (primarily negative peaks in frontal and positive peaks in parietal areas), but contribution of deep sources to sustained time-domain potentials (negativity in planning and positivity in execution). Transient and sustained ERD patterns in μ and β frequency bands of ear-lobe-referenced and surface Laplacian EEG indicate the contribution of both superficial and deep sources to ERD/ERS. As no physical displacement happens during the task, we can infer that the underlying mechanisms of motor-related ERPs and ERD/ERS patterns do not only depend on change in limb coordinate or muscle-length-dependent ascending sensory information and are primary generated by motor preparation, direction-dependent planning and execution of isometric motor tasks. The results contribute to our understanding of the functions of different brain regions during voluntary motor tasks and their activity signatures in EEG can shed light on the relationships between large-scale recordings such as EEG and other recordings such as single unit activity and fMRI in this context

Neuroergonomics applications of electroencephalography in physical activities : a systematic review

Recent years have seen increased interest in neuroergonomics, which investigates the brain activities of people engaged in diverse physical and cognitive activities at work and in everyday life. The present work extends upon prior assessments of the state of this art. However, here we narrow our focus specifically to studies that use electroencephalography (EEG) to measure brain activity, correlates, and effects during physical activity. The review uses systematically selected, openly published works derived from a guided search through peer-reviewed journals and conference proceedings. Identified studies were then categorized by the type of physical activity and evaluated considering methodological and chronological aspects via statistical and content-based analyses. From the identified works (n = 110), a specific number (n = 38) focused on less mobile muscular activities, while an additional group (n = 22) featured both physical and cognitive tasks. The remainder (n = 50) investigated various physical exercises and sporting activities and thus were here identified as a miscellaneous grouping. Most of the physical activities were isometric exertions, moving parts of upper and lower limbs, or walking and cycling. These primary categories were sub-categorized based on movement patterns, the use of the event-related potentials (ERP) technique, the use of recording methods along with EEG and considering mental effects. Further information on subjects' gender, EEG recording devices, data processing, and artifact correction methods and citations was extracted. Due to the heterogeneous nature of the findings from various studies, statistical analyses were not performed. These were thus included in a descriptive fashion. Finally, contemporary research gaps were pointed out, and future research prospects to address those gaps were discussed

EEG-based Signatures of Isometric Arm Forces by Females at Different Levels of Physical Exertion and Comfort

In recent years, electroencephalography (EEG) has become a valuable technique for ergonomics studies of physical activities and other real-life tasks. Since the perception of force exertion is influenced by various psychophysical, cognitive, and social factors, different subjective measures have been traditionally used to measure the perception of physical exertion and related body discomfort. Along with the subjective measures, research showed that neural signals are also necessary objective measures to understanding human perception of physical tasks. However, EEG signatures of different physical exertion levels and perceived physical comfort have not been explored. The main objective of this study was to investigate EEG activity measured by power spectral density (PSD) for isometric arm forces at different levels of physical exertion and physical comfort. The first part of the study investigated PSD changes at five predefined force exertion levels, i.e., extremely light, light, somewhat hard, hard, and extremely hard. The healthy female participants performed physical exertions and rated their level of experienced physical comfort. Significant differences in force exertion and PSD for theta, beta, and gamma waves were observed. Significant correlations were also found between PSD, force, and rating of physical comfort (RPPC). In the second part of the study, PSD changes at predefined physical comfort levels were investigated, namely at very low, moderate, fair, high, and very high comfort levels. The participants also rated the level of perceived physical exertion. Significant differences in force exertion and comfort levels for theta, beta, and gamma power were found. In addition, significant correlations were found between PSD, force, and rate of physical exertion (RPE). Overall, this is a novel study where EEG signatures of isometric efforts by females have been investigated at different force and physical comfort levels. The reported results should improve our understanding of the neural correlates of physical tasks performed by females

Topological Changes in the Functional Brain Networks Induced by Isometric Force Exertions Using a Graph Theoretical Approach: An EEG-based Neuroergonomics Study

Neuroergonomics, the application of neuroscience to human factors and ergonomics, is an emerging science focusing on the human brain concerning performance at work and in everyday settings. The advent of portable neurophysiological methods, including electroencephalography (EEG), has enabled measurements of real-time brain activity during physical tasks without restricting body movements. However, the EEG signatures of different physical exertion activity levels that involve the musculoskeletal system in everyday settings remain poorly understood. Furthermore, the assessment of functional connectivity among different brain regions during different force exertion levels remains unclear. One approach to investigating the brain connectome is to model the underlying mechanism of the brain as a complex network. This study applied employed a graph-theoretical approach to characterize the topological properties of the functional brain network induced by predefined force exertion levels, namely extremely light (EL), light (L), somewhat hard (SWH), hard (H), and extremely hard (EH) in two frequency bands, i.e., alpha and beta. Twelve female participants performed an isometric force exertion task and rated their perception of physical comfort at different physical exertion levels. A CGX-Mobile-64 EEG was used for recording spontaneous brain electrical activity. After preprocessing the EEG data, a source localization method was applied to study the functional brain connectivity at the source level. Subsequently, the alpha and beta networks were constructed by calculating the coherence between all pairs of 84 brain regions of interests that were selected using Brodmann Areas. Graph -theoretical measures were then employed to quantify the topological properties of the functional brain networks at different levels of force exertions at each frequency band. During an \u27extremely hard\u27 exertion level, a small-world network was observed for the alpha coherence network, whereas an ordered network was observed for the beta coherence network. The results suggest that high-level force exertions are associated with brain networks characterized by a more significant clustering coefficient, more global and local efficiency, and shorter characteristic path length under alpha coherence. The above suggests that brain regions are communicating and cooperating to a more considerable degree when the muscle force exertions increase to meet physically challenging tasks. The exploration of the present study extends the current understanding of the neurophysiological basis of physical efforts with different force levels of human physical exertion to reduce work-related musculoskeletal disorders

Measuring operator’s pain : toward evaluating Musculoskeletal disorder at work

Musculoskeletal disorders (MSDs) have affected an increasing number of people in the active general population. In this perspective, we developed a measuring tool taking muscle activities in certain regions of the body, standing posture taking the center of pressure under the feet and feet positions. This tool also comprises an instrumented helmet containing an electroencephalogram (EEG) to measure brain activity, and an accelerometer reporting the movements of the head. Then, our tool comprises both non-invasive instrumented insole and safety helmet. Moreover, the same tool measures muscular activities in specific regions of the body using an electromyogram (EMG). The aim is to combine all the data in order to identify consistent patterns between brain activity, postures, movements and muscle activity, and then, understand their connection to the development of MSDs. This paper presents three situations reported to be a risk for MSDs and an analysis of the signals is presented in order to differentiate adequate or abnormal posture

Mesures électrophysiologiques : indicateurs d’exposition aux microblessures anatomiques à risque de troubles musculo-squelettiques

Les troubles musculo-squelettiques (TMS) réfèrent à un ensemble de symptômes du système musculo-squelettique comme la douleur, la faiblesse musculaire, les gestes inappropriés, etc. Les TMS dans nos travaux de recherche, sont liés au travail et sont attribuables, entre autres, à des mouvements répétitifs ou à des cadences élevées, aux postures contraignantes ou prolongées, exposant les tissus anatomiques à une sur-sollicitation mécanique. Les TMS sont fréquemment observés chez les travailleurs manuels selon les rangs de « Prévention index ». Toutefois, sur un poste similaire, le rationnel du développement d’un TMS chez une personne et l’absence de TMS chez une autre personne demeure incertain. L’objectif du présent travail est d’identifier les paramètres musculaires (mesurables par un EMG) et d’activation cérébrale (mesurables par un EEG) pouvant constituer des déterminants personnels d’exposition aux microblessures musculaires. Notre hypothèse est que la sur-sollicitation tissulaire engendre des microblessures pouvant entraîner des TMS et que certaines personnes sont plus susceptibles aux microblessures, et donc plus à risque de développer un TMS. Pour ce faire, des données physiologiques (EEG, EMG) ont été collectées sur 12 participants jeunes adultes (26,83± 4,13 ans donc 2 femmes) en bonne santé opérants deux tâches simulées en posture debout dans deux situations de mesure : A) avec faible risque d’exposition aux microblessures (tâche servant de référence) et B) avec un risque plus prononcé exposition aux microblessures (tâche d’évaluation). Nous avons calculé la densité spectrale de puissance (DSP) des signaux à partir des signaux normalisés aussi bien pour l’EEG (ERD/ERS exprimé en %) que pour l’EMG (DSP exprimé en μv2). Une analyse de variance (ANOVA à mesures répétées) à trois facteurs a été conduite pour déterminer s’il y a des différences au travers des conditions expérimentales. Nos résultats montrent l’existence d’une différence significative au niveau des signaux physiologiques durant l’exécution des deux tâches. En particulier, il y a des déterminants personnels à l’origine de ces différences : une augmentation significative de la désynchronisation (ERD) des ondes bêta sur l’électrode temporale gauche durant la tâche à risque élevé (B) par rapport à la tâche à faible risque (A) de microblessures a été observée. De plus, une baisse non significative de la densité spectrale de puissance (DSP), de l’activité musculaire sur deltoïde droit a été observée dans les mêmes conditions. Ce travail pilote contribue à l’avancement d’une nouvelle approche de caractérisation des indicateurs d’exposition aux microblessures, basée sur les signaux physiologiques. Musculoskeletal disorders (MSDs) refer to a set of symptoms of the musculoskeletal system such as pain, muscle weakness, inappropriate gestures, etc. The MSDs in this research works are work-related and are attributable, among other things, to repetitive or high-speed movements, to constraining or prolonged postures, exposing anatomical tissues to mechanical overstretching. According to the ranks of "Prevention Index", among the top 20 sub-sectors at risk of MSD, almost all are found among manual workers. However, it is unclear why on a similar workstation, one person develops a TMS while another is free. The goal is to identify muscle parameters (EMG) and brain activation (EEG) that may be personal determinants of muscle micro-injury exposure. Our hypothesis is that tissue overload causes micro-injuries that can result in TMS and that some people are more susceptible to micro-injury; and therefore more at risk of developing a TMS. To do this, physiological data (EEG, EMG) were collected on 12 participants young adults (26,83 ± 4,13 years, two women) in good health during two simulated tasks in standing posture including operations A) with a low risk of exposure to micro-injuries (reference task) and B) with a greater risk of micro-injury exposure (evaluation task). We calculated the power spectral density (DSP) of the signals from the normalized signals for EEG (ERD / ERS expressed in%) as well as for EMG (DSP expressed in μv2) An analysis of variance (ANOVA to repeated measurements) to three factors was conducted to determine the differences across each experimental condition. Our results show the existence of a significant difference in physiological signals during the execution of two tasks. In particular, on the personal determinants at the origin of the differences, we see a significant increase in the desynchronization (ERD) of the beta waves on the left temporal electrode during the task at high-level risk (B) compared to the low-level risk task (A) of micro-injury. In addition, a nonsignificant decrease in power spectral density (DSP), muscle activity on the right deltoid was observed under the same conditions. Although our work is exploratory in nature, it contributes to the advancement of a new approach to characterization of exposure indicators to micro injuries based on physiological signals

Sensorimotor Modulations by Cognitive Processes During Accurate Speech Discrimination: An EEG Investigation of Dorsal Stream Processing

Internal models mediate the transmission of information between anterior and posterior regions of the dorsal stream in support of speech perception, though it remains unclear how this mechanism responds to cognitive processes in service of task demands. The purpose of the current study was to identify the influences of attention and working memory on sensorimotor activity across the dorsal stream during speech discrimination, with set size and signal clarity employed to modulate stimulus predictability and the time course of increased task demands, respectively. Independent Component Analysis of 64–channel EEG data identified bilateral sensorimotor mu and auditory alpha components from a cohort of 42 participants, indexing activity from anterior (mu) and posterior (auditory) aspects of the dorsal stream. Time frequency (ERSP) analysis evaluated task-related changes in focal activation patterns with phase coherence measures employed to track patterns of information flow across the dorsal stream. ERSP decomposition of mu clusters revealed event-related desynchronization (ERD) in beta and alpha bands, which were interpreted as evidence of forward (beta) and inverse (alpha) internal modeling across the time course of perception events. Stronger pre-stimulus mu alpha ERD in small set discrimination tasks was interpreted as more efficient attentional allocation due to the reduced sensory search space enabled by predictable stimuli. Mu-alpha and mu-beta ERD in peri- and post-stimulus periods were interpreted within the framework of Analysis by Synthesis as evidence of working memory activity for stimulus processing and maintenance, with weaker activity in degraded conditions suggesting that covert rehearsal mechanisms are sensitive to the quality of the stimulus being retained in working memory. Similar ERSP patterns across conditions despite the differences in stimulus predictability and clarity, suggest that subjects may have adapted to tasks. In light of this, future studies of sensorimotor processing should consider the ecological validity of the tasks employed, as well as the larger cognitive environment in which tasks are performed. The absence of interpretable patterns of mu-auditory coherence modulation across the time course of speech discrimination highlights the need for more sensitive analyses to probe dorsal stream connectivity

Continuous sensory-motor transformation and their electrophysiological signatures

Perceptual decisions require efficient transformation of sensory information to motor responses. Most laboratory-based research on decision-making consid- ered discrete and over-simplified actions. This thesis focused on human perfor- mance and electrophysiological signatures of continuous actions in response to decisions from three aspects. First, a systematic comparison between joystick movements and key presses showed that behavioural performance and under- lying cognitive processes are not affected by response modality, establishing the validity and consistency of using joystick trajectories to measure decision responses. Second, a behavioural paradigm was developed to integrate continu- ous circular joystick movements with perceptual decisions of coherent motion. The signal-to-noise ratio of sensory inputs has been shown to affect the ac- curacy and response time of ongoing actions, but its influence on movement speed diminished after substantial training. Multivariate pattern analysis on magnetoecephalography (MEG) data recorded during the experiment identi- fied stable information representations that sensitive to the quality of sensory information as well as the direction of periodic kinematics of circular move- ments. Furthermore, pattern information of complex actions was observed prior to movement onset, indicating the encoding of abstract preparatory ac- tion plans. Third, this thesis investigated the MEG signatures of circular joystick movements initiated via voluntary choices, instead of external sensory inputs. In a novel oddball paradigm, voluntarily choosing a continuous action built up an expectation of the statistical regularity of subsequent sensory in- puts. Violating that expectation via incongruent sensory information resulted in significant multivariate representation in MEG activity of the mismatch event. Overall results presented in this thesis highlighted how ongoing actions can be influenced by, and impact on, the continuous processing of sensory inputs in the human brai

Motor Adaptation to Muscle Fatigue: Moderating Factors and Implications

Muscle fatigue reduces the force that a muscle can produce and causes sensations of weakness and discomfort. People can adapt to muscle fatigue by adopting new movement patterns and control strategies. These motor adaptations can affect performance and sometimes predispose people to injuries. However, the effects of fatigue are situation-dependent. This research examined how the effects of muscle fatigue are moderated by which muscles are fatigued, the fatigue state, and the sensation of pain. It was expected that these moderating factors would affect the motor adaptations that people use when fatigued, the rate of muscle fatigue, and the risk of error and injury. Since different joints make different contributions to the completion of movement tasks, fatigue that is localized in different muscle groups is expected to affect movement differently. Aim 1 compared changes in whole-body movement coordination following fatigue of proximal and distal muscle groups in the upper extremity. Subjects maintained task performance after both proximal and distal fatigue. Proximal fatigue led to widespread movement changes across several joints, but distal fatigue primarily caused changes at the distal joints. The observed changes after proximal fatigue may increase the risk of back pain and injury, while changes after distal fatigue may predispose people to errors in manipulation. Muscle fatigue is a complex, multifactorial process, and people may adapt to fatigue by changing the movement patterns of many joints. It is difficult to quantify the effects of muscle fatigue on multi-joint coordination. In Aim 2, I used principal components analyses to determine how multi-joint coordination changes during and after muscle fatigue. During fatigue, inter-joint x coordination decreased, and subjects utilized a stiffening strategy that may have reduced the complexity of movement. However, these changes began to reverse after cessation of a fatiguing task. The observed changes suggest that people learn novel coordinative patterns as they adapt to muscle fatigue. Adapting to muscle fatigue is a cognitively demanding process. In working environments, biological stimuli such as pain may compete for limited cognitive resources during movement tasks. Aim 3 used a goal equivalent manifold (GEM) approach to determine how experimental pain influences the ability to adapt to muscle fatigue. Ischemic muscle pain in the contralateral arm caused people to reduce movement control, but this did not lead to significantly faster fatigue rates. However, order of the painful, and non-painful experimental sessions had a significant effect on fatigue rate. Furthermore, people who exhibit catastrophic thinking used different movement strategies than those who did not exhibit catastrophic thinking. Together these results demonstrate that the fatigue state of the muscles and the presence of a noxious stimulus moderate the way that people adapt to muscle fatigue. People can adapt to muscle fatigue by modifying their movement patterns, but motor adaptation does not necessarily lead to optimal movement strategies. While motor adaptation did not affect the task outcome in these or previous fatigue studies, the lack of performance deficits is likely attributable to the selection of simple experimental tasks in highly controlled environments. The moderating factors examined here are likely to affect complex fatiguing situations encountered in real world environments where the observed reduction in movement coordination and control could negatively impact task execution and lead to inefficient movement and injury. The current results emphasize the need to better understand how fatigue affects movement in realistic working environments.PHDKinesiologyUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/138532/1/jccowle_1.pd